🇳🇬 Outbreak Investigation of Acute Ascites
  • Overview
  • Case description
  • Exposures
Cases distribution in 🇳🇬 Sokoto
  • 📈 Cases per week and sex
  • 📈 Cases vs Controls per week
  • Age and Sex Distribution - Cases
  • Age and Sex Distribution - Controls
  • Digestive Symptoms by Sex - Cases
  • Digestive symptoms by Age - Cases
  • Digestive symptoms - Cases vs Controls
  • Demographics - Cases vs Controls
  • Reported Symptoms - Cases vs Controls
Variable

cases
N = 72

controls
N = 283

p-value 1
Age, n (%)

0.068
    7-27 days 0 (0%) 2 (0.8%)
    1-4 years 17 (24%) 28 (12%)
    5-9 years 33 (46%) 110 (46%)
    10-14 years 22 (31%) 97 (41%)
    Missing/Unknown 0 46
Sex, n (%)

0.5
    Male 42 (58%) 152 (64%)
    Female 30 (42%) 84 (35%)
    Unknown 0 (0%) 1 (0.4%)
    Missing/Unknown 0 46
1

Fisher’s exact test

Variable

cases
N = 72

controls
N = 283

p-value

1
Abdominal distention, n (%) 44 (98%) 4 (100%) >0.9
    Missing/Unknown 27 279
Abdominal pain, n (%) 42 (93%) 4 (100%) >0.9
    Missing/Unknown 27 279
Wheeze, n (%) 3 (75%) 0 (NA%)
    Missing/Unknown 68 283
Vomiting, n (%) 23 (51%) 4 (100%) 0.12
    Missing/Unknown 27 279
Cough, n (%) 2 (50%) 0 (NA%)
    Missing/Unknown 68 283
...with sputum, n (%) 1 (50%) 0 (NA%)
    Missing/Unknown 70 283
Diarrhoea, n (%) 15 (34%) 4 (100%) 0.020
    Missing/Unknown 28 279
Loss of appetite, n (%) 19 (42%) 0 (0%) 0.15
    Missing/Unknown 27 279
Any problem of gastrointestinal tract, n (%) 45 (63%) 4 (2.1%) <0.001
    Missing/Unknown 0 88
Fever, n (%) 21 (29%) 7 (3.3%) <0.001
    Missing/Unknown 0 70
Blood in stool, n (%) 2 (4.5%) 0 (0%) >0.9
    Missing/Unknown 28 279
Sweating or chills (day or night), n (%) 1 (1.4%) 5 (2.5%) >0.9
    Missing/Unknown 3 85
Any chest problem, n (%) 4 (5.7%) 2 (1.0%) 0.042
    Missing/Unknown 2 85
Pale stool, n (%) 1 (2.3%) 0 (0%) >0.9
    Missing/Unknown 28 279
Excessive salivation, n (%) 1 (2.3%) 0 (0%) >0.9
    Missing/Unknown 28 279
Any muscle or bone problem, n (%) 1 (1.4%) 0 (0%) 0.3
    Missing/Unknown 2 87
Any ear, nose or throat problem, n (%) 1 (1.4%) 0 (0%) 0.3
    Missing/Unknown 1 88

Only exposures with non-zero prevalence are shown.

1

Fisher’s exact test; Pearson’s Chi-squared test

Antibiotics use

57%
  • Reported Symptoms
  • Medical conditions
  • Vaccination
Variable Prevalence Percentage Frequency
Any problem of gastrointestinal tract 45
62.5%
45 / 72
Abdominal distention 44
97.8%
44 / 45
Abdominal pain 42
93.3%
42 / 45
Vomiting 23
51.1%
23 / 45
Fever 21
29.2%
21 / 72
Loss of appetite 19
42.2%
19 / 45
Diarrhoea 15
33.3%
15 / 45
Any chest problem 4
5.6%
4 / 72
Wheeze 3
75%
3 / 4
Blood in stool 2
4.4%
2 / 45
Cough 2
50%
2 / 4
Breathlessness 2
100%
2 / 2
Sweating or chills (day or night) 1
1.4%
1 / 72
Pale stool 1
2.2%
1 / 45
Excessive salivation 1
2.2%
1 / 45
Any muscle or bone problem 1
1.4%
1 / 72
Any ear, nose or throat problem 1
1.4%
1 / 72
...with sputum 1
50%
1 / 2
Pain in mouth 1
100%
1 / 1
Runny nose 1
100%
1 / 1
Swallowing problem 1
100%
1 / 1
Difficult swallow 1
100%
1 / 1
Painful swallow 1
100%
1 / 1
Fatigue or malaise 1
100%
1 / 1
Muscle pain or aching 1
100%
1 / 1
.. duration 0
0%
0 / 45
Any neurological problems 0
0%
0 / 72
Any eye problem 0
0%
0 / 72
...with blood 0
0%
0 / 24
Altered level of consciousness 0
0%
0 / 2
Seizures 0
0%
0 / 1
Pain or redness in the eye 0
0%
0 / 1
Sore throat 0
0%
0 / 1
Muscle cramps 0
0%
0 / 1
Variable Prevalence Percentage Frequency
Tuberculosis (active) 1
1.4%
1 / 71
Congenital anomaly 0
0%
0 / 72
Chronic heart disease 0
0%
0 / 71
Chronic lung disease 0
0%
0 / 71
Chronic neurologic condition 0
0%
0 / 72
Chronic liver disease 0
0%
0 / 71
Chronic kidney disease 0
0%
0 / 71
Diabetes 0
0%
0 / 72
Hematological Disorders 0
0%
0 / 72
HIV 0
0%
0 / 70
Cancer 0
0%
0 / 72
Other immunosuppressive condition 0
0%
0 / 72
Variable Prevalence Percentage Frequency
Yellow fever 6
8.3%
6 / 72
IPV 5
6.9%
5 / 72
BCG 5
6.9%
5 / 72
Hepatitis A vaccine 1
1.4%
1 / 72
Hepatitis B vaccine 1
1.4%
1 / 72
Rotavirus 1
1.4%
1 / 72
Mumps and Rubella (MMR) 0
0%
0 / 72
  • Food exposures prior to hospital admission - Cases
  • Food exposures prior to hospital admission - Controls
  • Exposure to medication prior to hospital admission - Cases vs Controls
  • Other exposures prior to hospital admission - Cases vs Controls

Variable

cases
N = 72

controls
N = 283

p-value

1
Antibiotics, n (%) 39 (56%) 2 (0.8%) <0.001
    Missing/Unknown 2 46
Paracetamol/acetaminophen, n (%) 6 (8.5%) 2 (0.8%) 0.002
    Missing/Unknown 1 46
Other medications, n (%) 4 (5.6%) 0 (0%) 0.003
    Missing/Unknown 1 46
Cough Medicine, n (%) 1 (1.4%) 0 (0%) 0.2
    Missing/Unknown 1 48

Only exposures with non-zero prevalence are shown.

1

Pearson’s Chi-squared test; Fisher’s exact test

Variable

cases
N = 72

controls
N = 283

p-value

1
Access to a latrine or toilet, n (%) 69 (100%) 189 (93%) 0.015
    Missing/Unknown 3 79
Does the patient frequently handle or come in contact with soil or sand?, n (%) 47 (69%) 48 (29%) <0.001
    Missing/Unknown 4 115
Any outbreaks reported by school or day care prior to symptom onset, n (%) 3 (33%) 1 (33%) >0.9
    Missing/Unknown 63 280
Do you keep any animals as pets or domestic animals, n (%) 26 (37%) 43 (24%) 0.035
    Missing/Unknown 2 103
Any new illnesses or infections in household members or other close contacts prior to symptom onset, n (%) 13 (18%) 8 (4.3%) <0.001
    Missing/Unknown 1 96
Attendance to in-person school or day care prior to symptom onset, n (%) 9 (13%) 3 (1.6%) <0.001
    Missing/Unknown 3 99
Any contact with wild animals at the time of the illness, n (%) 8 (12%) 2 (1.1%) <0.001
    Missing/Unknown 4 98
Does anyone smoke cigarettes or tobacco inside any building where you work or spend other time?, n (%) 5 (7.5%) 4 (2.5%) 0.13
    Missing/Unknown 5 122
Any contact with stray animals, n (%) 5 (7.1%) 2 (1.1%) 0.018
    Missing/Unknown 2 98
Does anyone smoke cigarettes or tobacco inside the building where you sleep (do not include yourself)?, n (%) 2 (2.9%) 2 (1.2%) 0.6
    Missing/Unknown 4 119
Any animal bite/scracth prior to symptoms onset, n (%) 2 (2.9%) 0 (0%) 0.070
    Missing/Unknown 4 96

Only exposures with non-zero prevalence are shown.

1

Fisher’s exact test; Pearson’s Chi-squared test

  • Exposure to medication prior to hospital admission
  • Other exposures prior to hospital admission
Variable Prevalence Percentage Frequency
Antibiotics 39
54.2%
39 / 72
Paracetamol/acetaminophen 6
8.3%
6 / 72
Other medications 4
5.6%
4 / 72
Cough Medicine 1
1.4%
1 / 72
Allergy medicine 0
0%
0 / 72
Aspirin 0
0%
0 / 72
Ibuprofen 0
0%
0 / 72
Herbal medicine/naturopathic/homeopathic medicine 0
0%
0 / 72
Variable Prevalence Percentage Frequency
Access to a latrine or toilet 69
95.8%
69 / 72
Does the patient frequently handle or come in contact with soil or sand? 47
65.3%
47 / 72
Do you keep any animals as pets or domestic animals 26
36.1%
26 / 72
Any new illnesses or infections in household members or other close contacts prior to symptom onset 13
18.1%
13 / 72
Attendance to in-person school or day care prior to symptom onset 9
12.5%
9 / 72
Any contact with wild animals at the time of the illness 8
11.1%
8 / 72
Does anyone smoke cigarettes or tobacco inside any building where you work or spend other time? 5
6.9%
5 / 72
Any contact with stray animals 5
6.9%
5 / 72
Any outbreaks reported by school or day care prior to symptom onset 3
30%
3 / 10
Does anyone smoke cigarettes or tobacco inside the building where you sleep (do not include yourself)? 2
2.8%
2 / 72
Any animal bite/scracth prior to symptoms onset 2
2.8%
2 / 72
Any problem or exposure to different water prior to symptom onset 0
0%
0 / 72
Did the patient or household member start using any new personal care products (e.g. soaps, lotions) prior to symptom onset? 0
0%
0 / 72
Any national or overseas trip prior to symptom onset 0
0%
0 / 72
  • Antibiotics exposure
  • Pets/domestic animals exposure
  • Type of latrine or toilet


This dashboard displays statistics of reported cases of ascites in 🇳🇬 as of 2025-03-27

Total cases 72
Total controls 283
Female cases 42%
Persons with HIV 0
Below 5 yrs 24%

Disclaimer

Data are provided by many contributors through the the WHO Clinical data platform and are not necessarily representative. To become a contributor, please see the terms of use and register here.